Sungmin Kang

Ph.D. student at KAIST


I am a Ph.D. student researching software engineering: specifically, I use machine learning to build tools to help developers remove bugs from software. My research focuses on facilitating the debugging process from the perspective of the developer. For example, I have contributed towards automatically reproducing bug reports and explainable automated debugging. I have also contributed to the theory of the field by analyzing existing techniques using a novel Bayesian statistics framework.

Currently, I am advised by Dr. Shin Yoo in the COINSE research group at Korea Advanced Institute of Science and Technology.


Nov 4, 2023 I started this blog! :four_leaf_clover:

latest posts

selected publications

  1. A Quantitative and Qualitative Evaluation of LLM-based Explainable Fault Localization
    Sungmin KangGabin An, and Shin Yoo
    In Proceedings of the 32nd ACM International Conference on the Foundations of Software Engineering, 2024
  2. bapp_thumbnail.png
    A Bayesian Framework for Automated Debugging
    Sungmin Kang, Wonkeun Choi, and Shin Yoo
    In Proceedings of the 32nd International Symposium on Software Testing and Analysis, 2023
  3. libro_thumbnail.png
    Large Language Models are Few-shot Testers: Exploring LLM-based General Bug Reproduction
    Sungmin KangJuyeon Yoon, and Shin Yoo
    In Proceedings of the 45th IEEE/ACM International Conference on Software Engineering, 2023